Conversion of Object-Related Traffic Sensor Information at Roadways and Intersections for Virtual Dynamic Digital Representation of Objects

2. The method of claim 1, further comprising overlaying the object animation data onto the map for visualization of the information collected by the traffic detection system as a dynamic animation of the traffic environment on the display interface.

3. The method of claim 1, wherein the information collected by a traffic detection system is sensor data collected by one or more sensors.

4. The method of claim 3, wherein the one or more sensors include at least one of an imaging system, a radar system, a loop sensor, a magnetometer, a piezo sensor, an acoustic sensor, and ultrasonic sensor, and an air pressure sensor.

5. The method of claim 1, wherein the parsing the information collected by the traffic detection system to identify characteristics of the one or more specific objects further comprises filtering the information collected from the traffic detection system according to a type of sensor, and identifying a native frame rate of each type of sensor.

6. The method of claim 1, wherein the parsing the information collected by the traffic detection system to identify characteristics of the one or more specific objects further comprises identifying the type of sensor capturing each object, and identifying the positional coordinates of the sensor capturing each object and positional coordinates of each type of sensor in the traffic detection system.

7. The method of claim 1, further comprising classifying each object as one or more of a bicycle, a motorcycle, a truck, a passenger vehicle, a commercial vehicle, a pedestrian, and an incident to determine the object type.

8. The method of claim 1, wherein the characterizing the location data further comprises tracking a trajectory of each object by identifying a series of locations relative to the reference point, identifying a native capture time of the sensor generating the information for each object, correlating the series of locations to the native capture time, and sequencing the series of locations by a time interval between different locations based on the geospatial coordinates.

9. The method of claim 1, further comprising generating one or more icons on the dynamic animation of the traffic environment depicting the one or more the specific objects.

10. The method of claim 1, wherein the traffic environment is at least one of a signalized intersection, a roadway, a bicycle path, a pedestrian path, and a highway.

12. The system of claim 11, wherein the mapping and animation element is further configured to overlay the object animation data onto the map for visualization of the information collected by the traffic detection system as a dynamic animation of the traffic environment on the display interface.

13. The system of claim 11, wherein the one or more sensors include at least one of an imaging system, a radar system, a loop sensor, a magnetometer, a piezo sensor, an acoustic sensor, and ultrasonic sensor, and an air pressure sensor.

14. The system of claim 11, wherein the data preparation and curation element is further configured to filter the information collected from the traffic detection system according to a type of sensor and identify a native frame rate of each type of sensor.

15. The system of claim 11, wherein the data preparation and curation element is further configured to identify the type of sensor capturing each object, and identify the positional coordinates of the sensor capturing each object and positional coordinates of each type of sensor in the traffic detection system.

16. The system of claim 11, wherein the data preparation and curation element is further configured to classify each object as one or more of a bicycle, a motorcycle, a truck, a passenger vehicle, a commercial vehicle, a pedestrian, and an incident to determine the object type.

17. The system of claim 11, wherein the translation element is further configured to track a trajectory of each object by identifying a series of locations relative to the reference point, identifying a native capture time of the sensor generating the information for each object, correlating the series of locations to the native capture time, and sequencing the series of locations by a time interval between different locations based on the geospatial coordinates.

18. The system of claim 11, wherein the mapping and animation element is further configured to generate one or more icons on the dynamic animation of the traffic environment depicting the one or more the specific objects.

19. The system of claim 11, wherein the traffic environment is at least one of a signalized intersection, a roadway, a bicycle path, a pedestrian path, and a highway.

21. The method of claim 20, further comprising overlaying the object animation data onto a map for visualization of the information collected by the traffic detection system as a dynamic animation of the traffic environment.

22. The method of claim 20, wherein the one or more sensors include at least one of an imaging system, a radar system, a loop sensor, a magnetometer, a piezo sensor, an acoustic sensor, and ultrasonic sensor, and an air pressure sensor.

23. The method of claim 20, wherein the preparing input data collected by a traffic detection system further comprises filtering the input data according to a type of sensor and identifying a native frame rate of each type of sensor.

24. The method of claim 20, wherein the preparing input data collected by a traffic detection system further comprises identifying the type of sensor capturing each object, and identifying the positional coordinates of the sensor capturing each object and positional coordinates of each type of sensor in the traffic detection system.

25. The method of claim 20, further comprising classifying each object as one or more of a bicycle, a motorcycle, a truck, a passenger vehicle, a commercial vehicle, a pedestrian, and an incident to determine the object type.

26. The method of claim 20, wherein the translating a curated set of the parsed information further comprises tracking a trajectory of each object by identifying a series of locations relative to the reference point, identifying a native capture time of the sensor generating the information for each object, correlating the series of locations to the native capture time, and sequencing the series of locations by a time interval between different locations based on the geospatial coordinates.

27. The method of claim 20, further comprising generating one or more icons on the dynamic animation of the traffic environment depicting the one or more the specific objects.

28. The method of claim 20, wherein the traffic environment is at least one of a signalized intersection, a roadway, a bicycle path, a pedestrian path, and a highway.